Recently, a learning system such as a neural network has been applied to an alphabetical font recognition, a pattern recognition such as an image recognition, and control of an adaptation filter of a robot. However, in a learning system requiring teacher data, since it is difficult or even impossible to manually create teacher data, a learning system which automatically adapts to an outside environment is sought.
A neural network as a learning system capable of learning a desired pattern is applied in a wide variety of fields. A hierarchical neural network of a perception comprises three hierarchies, e.g. an input hierarchy, an intermediate hierarchy, and an output hierarchy. The output hierarchy outputs an output pattern in response to an input pattern to the input hierarchy. To enable the network to output a proper output pattern for an input pattern, a learning of a neural network is performed using a desired pattern. That is, a weight in the neural network is determined, e.g. by a back propagation method, so that a proper output pattern is presented for an input pattern and a proper output pattern is outputted. Thus, conventionally, the neural network performs its learning by using the desired pattern manually prepared beforehand.
However, in an actual application there are at least three patterns, a pattern related to a time series, a pattern whose desired pattern itself changes and a pattern for an unpredictable state. Problems arise such as the difficulty in determining the variety and quantity of the patterns prepared as desired patterns and the high time consumption of a desired pattern. Hence, to create a practical learning system in an actual application, an algorithm is required that enables the learning system itself to correspond with the input pattern and the output pattern, the corresponding input pattern to be evaluated according to an internal evaluation standard maintained in its own system, and the proper input or output pattern to be learned as the desired pattern.
Further, in a system capable of creating a desired pattern according to the internal evaluation standard, in case of a method without an interface for receiving an external evaluation for the output of the system itself, the system must be equipped with a predetermined internal evaluation standard. Therefore, when the system is applied to a variety of fields, problems exist. For example, the internal evaluation standard must be changed according to the particular application field resulting in a clock of system flexibility.
Therefore, a system is sought which has an interface for external evaluation, capable of self earning the evaluation standard of the external evaluation.